Tools

"... Abstract—As an object moves through the field of view of a camera, the images of the object may change dramatically. This is not simply due to the translation of the object across the image plane. Rather, complications arise due to the fact that the object undergoes changes in pose relative to the v ..."

Abstract—As an object moves through the field of view of a camera, the images of the object may change dramatically. This is not simply due to the translation of the object across the image plane. Rather, complications arise due to the fact that the object undergoes changes in pose relative to the viewing camera, changes in illumination relative to light sources, and may even become partially or fully occluded. In this paper, we develop an efficient, general framework for object tracking—one which addresses each of these complications. We first develop a computationally efficient method for handling the geometric distortions produced by changes in pose. We then combine geometry and illumination into an algorithm that tracks large image regions using no more computation than would be required to track with no accommodation for illumination changes. Finally, we augment these methods with techniques from robust statistics and treat occluded regions on the object as statistical outliers. Throughout, we present experimental results performed on live video sequences demonstrating the effectiveness and efficiency of our methods. Index Terms—Visual tracking, real-time vision, illumination, motion estimation, robust statistics.

"... Simultaneous inference is a common problem in many areas of application. If multiple null hypotheses are tested simultaneously, the probability of rejecting erroneously at least one of them increases beyond the pre-specified significance level. Simultaneous inference procedures have to be used which ..."

which adjust for multiplicity and thus control the overall type I error rate. In this paper we describe simultaneous inference procedures in general parametricmodels, where the experimental questions are specified through a linear combination of elemental model parameters. The framework described here

"... This paper examines the role of parametric modeling as an application for the global computing grid, and explores some heuristics which make it possible to specify soft real time deadlines for larger computational experiments. We demonstrate the scheme with a case study utilizing the Globus toolkit ..."

This paper examines the role of parametricmodeling as an application for the global computing grid, and explores some heuristics which make it possible to specify soft real time deadlines for larger computational experiments. We demonstrate the scheme with a case study utilizing the Globus toolkit

by
Alexei Efros, Thomas Leung
- In International Conference on Computer Vision, 1999

"... A non-parametric method for texture synthesis is proposed. The texture synthesis process grows a new image outward from an initial seed, one pixel at a time. A Markov random field model is assumed, and the conditional distribution of a pixel given all its neighbors synthesized so far is estimated by ..."

A non-parametric method for texture synthesis is proposed. The texture synthesis process grows a new image outward from an initial seed, one pixel at a time. A Markov random field model is assumed, and the conditional distribution of a pixel given all its neighbors synthesized so far is estimated

"... Several parametric representations of the acoustic signal were compared as to word recognition performance in a syllable-oriented continuous speech recognition system. The vocabulary in-cluded many phonetically similar monosyllabic words, therefore the emphasis was on ability to retain phonetically ..."

Several parametric representations of the acoustic signal were compared as to word recognition performance in a syllable-oriented continuous speech recognition system. The vocabulary in-cluded many phonetically similar monosyllabic words, therefore the emphasis was on ability to retain

"... Time varying correlations are often estimated with Multivariate Garch models that are linear in squares and cross products of the data. A new class of multivariate models called dynamic conditional correlation (DCC) models is proposed. These have the flexibility of univariate GARCH models coupled wi ..."

with parsimonious parametricmodels for the correlations. They are not linear but can often be estimated very simply with univariate or two step methods based on the likelihood function. It is shown that they perform well in a variety of situations and provide sensible empirical results.

"... Standardized modular bridges improve the productivity of automation in design and fabrication in response to the variety of influence factors. In this study, optimized design models through the development process of a new structural system were constructed using Building Information Modeling (BIM) ..."

) technologies. The models consider design specifications, constructability and optimized detailing. Parametricmodeling was conducted to accommodate variation of each design values of the modular bridge structures such as bridge width, girder spacing and height of the pier. Each module by parametricmodeling

"... Nowadays, many commercial CAD systems support history-based, constraint-based and feature-based modelling. The use of these new capabilities raises the issue of persistent naming which refers to the problem of identifying entities in an initial parametric model and matching them in the re-evaluate ..."

Nowadays, many commercial CAD systems support history-based, constraint-based and feature-based modelling. The use of these new capabilities raises the issue of persistent naming which refers to the problem of identifying entities in an initial parametricmodel and matching them in the re